package cn._51doit.flink.day02.transformations;

import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.typeinfo.TypeHint;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

/**
 * 使用lambda表达式完成flatMap
 *
 *
 */
public class FlatMapDemo {

    public static void main(String[] args) throws Exception {

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        //hadoop flink hadoop spark
        DataStreamSource<String> lines = env.socketTextStream("localhost", 8888);

        //(hadoop, 1)
        //(flink, 1)
        //(hadoop, 1)
//        SingleOutputStreamOperator<Tuple2<String, Integer>> wordAndOne = lines.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {
//            @Override
//            public void flatMap(String line, Collector<Tuple2<String, Integer>> collector) throws Exception {
//                for (String word : line.split(" ")) {
//                    collector.collect(Tuple2.of(word, 1));
//                }
//            }
//        });

        SingleOutputStreamOperator<Tuple2<String, Integer>> wordAndOne = lines.flatMap((String line, Collector<Tuple2<String, Integer>> out) -> {
            String[] words = line.split(" ");
            for (String word : words) {
                out.collect(Tuple2.of(word, 1));
            }
        }).returns(TypeInformation.of(new TypeHint<Tuple2<String, Integer>>() {}));


        wordAndOne.print();

        env.execute();
    }

}
